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https://github.com/PaddlePaddle/FastDeploy.git
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6343b0db47
* Add notes for tensors * Optimize some apis * move some warnings * Support build with Paddle2ONNX * Add protobuf support * Fix compile on mac * add clearn package script * Add paddle2onnx code * remove submodule * Add onnx ocde * remove softlink * add onnx code * fix error * Add cmake file * fix patchelf * update paddle2onnx * Delete .gitmodules --------- Co-authored-by: PaddleCI <paddle_ci@example.com> Co-authored-by: pangyoki <pangyoki@126.com> Co-authored-by: jiangjiajun <jiangjiajun@baidu.lcom>
108 lines
3.3 KiB
C++
108 lines
3.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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/*
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* SPDX-License-Identifier: Apache-2.0
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*/
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#pragma once
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// Before:
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// B = Unsqueeze(Constant, axes)
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// After:
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// B = Constant (Constant with new shape)
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#include <numeric>
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#include "onnx/defs/tensor_util.h"
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#include "onnxoptimizer/pass.h"
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namespace ONNX_NAMESPACE {
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namespace optimization {
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struct FuseConstantUnsqueeze final : public PredicateBasedPass {
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explicit FuseConstantUnsqueeze()
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: PredicateBasedPass(PassType::Fuse, PassEfficiency::Complete,
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PassOptimizationType::Compute) {}
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std::string getPassName() const override { return "fuse_constant_unsqueeze"; }
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bool patternMatchPredicate(Node* node) override {
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return node->kind() == kUnsqueeze &&
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node->inputs()[0]->node()->kind() == kConstant;
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}
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bool runTransform(Node* n, Graph& graph,
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NodeDestroyType& destroy_current) override {
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destroy_current = NodeDestroyType::DestroyZero;
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// check if Constant is only used by Reshape
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if (n->inputs()[0]->uses().size() > 1) {
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return false;
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}
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Node* unsqueeze = n;
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Node* constant = n->inputs()[0]->node();
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// Process 'axes' data
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std::vector<int64_t> axes;
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if (unsqueeze->hasAttribute(kaxes)) {
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// opset 13 below
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axes = unsqueeze->is(kaxes);
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} else {
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// opset 13 and above - first check if 'unsqueeze' has 'axes' input
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// constant
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if (unsqueeze->inputs()[1]->node()->kind() != kConstant) {
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return false;
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}
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if (unsqueeze->inputs()[1]->uses().size() > 1) {
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return false;
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}
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Node* axes_const = unsqueeze->inputs()[1]->node();
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Tensor t = axes_const->t(kvalue);
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axes = ParseData<int64_t>(&t);
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}
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Tensor t = constant->t(kvalue);
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const auto& ori_size = t.sizes();
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for (size_t i = 0; i < axes.size(); ++i) {
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if (axes[i] < 0) {
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axes[i] = axes[i] + ori_size.size() + i + 1;
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}
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}
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std::vector<int64_t> new_size(ori_size.begin(), ori_size.end());
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for (size_t i = 0; i < axes.size(); ++i) {
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new_size.insert(new_size.begin() + axes[i], 1);
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}
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t.sizes().clear();
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t.sizes().insert(t.sizes().begin(), new_size.begin(),
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new_size.begin() + new_size.size());
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constant->t_(kvalue, std::move(t));
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// update constant node
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constant->output()->setSizes(unsqueeze->output()->sizes());
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constant->output()->setElemType(unsqueeze->output()->elemType());
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const bool replacing_success =
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tryReplacingAllUsesWith(unsqueeze->output(), unsqueeze->inputs()[0]);
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if (!replacing_success) {
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return false;
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}
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destroy_current = NodeDestroyType::DestroyOne;
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return true;
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}
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};
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} // namespace optimization
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} // namespace ONNX_NAMESPACE
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